An advanced introduction to computational molecular biology, using an applied algorithms approach. The first part of the course will cover established algorithmic methods, including pairwise sequence alignment and dynamic programming, multiple sequence alignment, fast database search heuristics, hidden Markov models for molecular motifs and phylogeny reconstruction. The second part of the course will explore emerging computational problems driven by the newest genomic research. Course work includes four to six problem sets, one midterm and final exam. A project based on recent results from the genomics literature will be required of students taking 03-711/15-856. Next fall, the primary text will be "Biological Sequence Analysis; Probabilistic Models of Proteins and Nucleic Acids", R. Durbin et al. This will be supplemented by class notes and articles from the primary literature.